
"""simple docstring"""


import itertools
import string
from collections.abc import Generator, Iterable



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_					)->				Generator[tuple[str, ...], None, None]:







       """simple docstring"""
       UpperCamelCase       			=		iter(UpperCAmelCase_					)
       while True:
              UpperCamelCase       			=		tuple(itertools.islice(UpperCAmelCase_		,   UpperCAmelCase_					)					)
              if not chunk:
                     return
              yield chunk



def 						lowerCamelCase__      (				UpperCAmelCase_					)->				str:







       """simple docstring"""
       UpperCamelCase       			=		"".join([c.upper() for c in dirty if c in string.ascii_letters]					)
       UpperCamelCase       			=		""

       if len(UpperCAmelCase_					) < 2:
              return dirty

       for i in range(len(UpperCAmelCase_					) - 1					):
              clean += dirty[i]

              if dirty[i] == dirty[i + 1]:
                     clean += "X"

       clean += dirty[-1]

       if len(UpperCAmelCase_					) & 1:
              clean += "X"

       return clean



def 						lowerCamelCase__      (				UpperCAmelCase_					)->				list[str]:







       """simple docstring"""
       # I and J are used interchangeably to allow
       # us to use a 5x5 table (25 letters)
       UpperCamelCase       			=		"ABCDEFGHIKLMNOPQRSTUVWXYZ"
       # we're using a list instead of a '2d' array because it makes the math
       # for setting up the table and doing the actual encoding/decoding simpler
       UpperCamelCase       			=		[]

       # copy key chars into the table if they are in `alphabet` ignoring duplicates
       for char in key.upper():
              if char not in table and char in alphabet:
                     table.append(UpperCAmelCase_					)

    # fill the rest of the table in with the remaining alphabet chars
       for char in alphabet:
              if char not in table:
                     table.append(UpperCAmelCase_					)

       return table



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_					)->				str:







       """simple docstring"""
       UpperCamelCase       			=		generate_table(UpperCAmelCase_					)
       UpperCamelCase       			=		prepare_input(UpperCAmelCase_					)
       UpperCamelCase       			=		""

       # https://en.wikipedia.org/wiki/Playfair_cipher#Description
       for chara, chara in chunker(UpperCAmelCase_		,   2					):
              UpperCamelCase			,							UpperCamelCase       			=		divmod(table.index(UpperCAmelCase_					)		,   5					)
              UpperCamelCase			,							UpperCamelCase       			=		divmod(table.index(UpperCAmelCase_					)		,   5					)

              if rowa == rowa:
                     ciphertext += table[rowa * 5 + (cola + 1) % 5]
                     ciphertext += table[rowa * 5 + (cola + 1) % 5]
              elif cola == cola:
                     ciphertext += table[((rowa + 1) % 5) * 5 + cola]
                     ciphertext += table[((rowa + 1) % 5) * 5 + cola]
              else:  # rectangle
                     ciphertext += table[rowa * 5 + cola]
                     ciphertext += table[rowa * 5 + cola]

       return ciphertext



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_					)->				str:







       """simple docstring"""
       UpperCamelCase       			=		generate_table(UpperCAmelCase_					)
       UpperCamelCase       			=		""

       # https://en.wikipedia.org/wiki/Playfair_cipher#Description
       for chara, chara in chunker(UpperCAmelCase_		,   2					):
              UpperCamelCase			,							UpperCamelCase       			=		divmod(table.index(UpperCAmelCase_					)		,   5					)
              UpperCamelCase			,							UpperCamelCase       			=		divmod(table.index(UpperCAmelCase_					)		,   5					)

              if rowa == rowa:
                     plaintext += table[rowa * 5 + (cola - 1) % 5]
                     plaintext += table[rowa * 5 + (cola - 1) % 5]
              elif cola == cola:
                     plaintext += table[((rowa - 1) % 5) * 5 + cola]
                     plaintext += table[((rowa - 1) % 5) * 5 + cola]
              else:  # rectangle
                     plaintext += table[rowa * 5 + cola]
                     plaintext += table[rowa * 5 + cola]

       return plaintext







"""simple docstring"""


import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin



class 	__a	(   _lowerCAmelCase     ,  _lowerCAmelCase     ,  _lowerCAmelCase						):






       @register_to_config
       def __init__(	self			:				Union[str, Any]							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				float							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				str							,   UpperCAmelCase_			:				bool = False							,   )->	str:







              """simple docstring"""
              super().__init__()

              UpperCamelCase       			=		nn.Embedding(UpperCAmelCase_							,   UpperCAmelCase_      )

              UpperCamelCase       			=		nn.Embedding(UpperCAmelCase_							,   UpperCAmelCase_      )
              UpperCamelCase       			=		False

              UpperCamelCase       			=		nn.Dropout(p=UpperCAmelCase_      )

              UpperCamelCase       			=		TaConfig(
                  vocab_size=UpperCAmelCase_							,   d_model=UpperCAmelCase_							,   num_heads=UpperCAmelCase_							,   d_kv=UpperCAmelCase_							,   d_ff=UpperCAmelCase_							,   dropout_rate=UpperCAmelCase_							,   feed_forward_proj=UpperCAmelCase_							,   is_decoder=UpperCAmelCase_							,   is_encoder_decoder=UpperCAmelCase_							,   )

              UpperCamelCase       			=		nn.ModuleList()
              for lyr_num in range(UpperCAmelCase_      ):
                     UpperCamelCase       			=		TaBlock(UpperCAmelCase_      )
                     self.encoders.append(UpperCAmelCase_      )

              UpperCamelCase       			=		TaLayerNorm(UpperCAmelCase_      )
              UpperCamelCase       			=		nn.Dropout(p=UpperCAmelCase_      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				int							,   UpperCAmelCase_			:				int							,   UpperCAmelCase_			:				str      )->	List[Any]:







              """simple docstring"""
              UpperCamelCase       			=		self.token_embedder(UpperCAmelCase_      )

              UpperCamelCase       			=		encoder_input_tokens.shape[1]
              UpperCamelCase       			=		torch.arange(UpperCAmelCase_							,   device=encoder_input_tokens.device      )
              x += self.position_encoding(UpperCAmelCase_      )

              UpperCamelCase       			=		self.dropout_pre(UpperCAmelCase_      )

              # inverted the attention mask
              UpperCamelCase       			=		encoder_input_tokens.size()
              UpperCamelCase       			=		self.get_extended_attention_mask(UpperCAmelCase_							,   UpperCAmelCase_      )

              for lyr in self.encoders:
                     UpperCamelCase       			=		lyr(UpperCAmelCase_							,   UpperCAmelCase_      )[0]
              UpperCamelCase       			=		self.layer_norm(UpperCAmelCase_      )

              return self.dropout_post(UpperCAmelCase_      ), encoder_inputs_mask





